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AI-Driven Model for Coordinated Development Between Regional Ecology and Economic Stability

Author

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  • Kun Zheng

    (College of Rural Revitalization, Fujian Agriculture and Forestry University, China)

  • Heliang Huang

    (College of Economics and Management, Fujian Agriculture and Forestry University, China)

Abstract

This study proposes an IoT-enabled artificial intelligence model to achieve coordinated ecological and socio-economic development in Fujian Province, China. By integrating real-time environmental monitoring through IoT sensor networks with Gradient Boosting Machine (GBM) algorithms, the framework provides dynamic assessment and prediction of ecological and economic indicators. A dual-layer evaluation index system, constructed using the entropy weight method, captures the interdependencies between environmental quality and economic growth. Empirical results from 2010–2020 show that the proposed model achieves high predictive accuracy (95.8%) and effectively identifies stages of ecological-economic coordination. The findings reveal a steady improvement in regional collaboration, with Fujian moving toward coordinated development despite ecological pressures. The study contributes to agricultural and environmental information systems by offering a replicable, data-driven approach that supports sustainable planning and policy-making.

Suggested Citation

  • Kun Zheng & Heliang Huang, 2025. "AI-Driven Model for Coordinated Development Between Regional Ecology and Economic Stability," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global Scientific Publishing, vol. 16(1), pages 1-30, January.
    • Handle: RePEc:igg:jaeis0:v:16:y:2025:i:1:p:1-30
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